Blood biomarkers of the late phase asthmatic response using RNA-Seq
Bibliographic record
Abstract
Asthmatic individuals respond differently, but reproducibly, to allergen inhalation challenge. Some individuals develop an isolated early response (ER), while others develop a dual response (DR). Peripheral blood cell transcriptome signatures can discriminate isolated early responders from dual asthmatic responders undergoing allergen inhalation challenge. 35 individuals (17 ERs and 18 DRs) participated in the allergen inhalation challenge. Blood samples were obtained prior to and 2 hours post allergen inhalation challenge. HiSeq-Illumina paired-ends 100bp sequencing was performed. A UCSC transcriptome using both the UCSC gene and gene-isoform transcripts was created using the RSEM (RNA-Seq by Expectation Maximization) package. RSEM uses Bowtie to align read files to the reference transcripts and estimates the expected number of counts per transcript. The biomarker pipeline consisted of 20x5-fold deep cross-validation using limma voom (linear models for microarrays and RNA-Seq using variance modeling at the observational level) for differential expression and elastic net for classification. Gene set enrichment analysis was performed using GeneGo. Classification performance of the pre-challenge classifier across the 100 panels included an AUC of 0.76±0.02, a sensitivity of 0.70±0.03 and a specificity of 0.72±0.02. There were 511 gene transcripts identified across the 100 panels. Pathway analysis of the 511 gene transcripts identified lectin induced complement pathway, integrin inside-out signaling, alternative complement pathway and function of MEF2 in T lymphocytes as the top ranked pathways. Classification performance of the post-challenge classifier across the 100 panels included an AUC of 0.62±0.002, a sensitivity of 0.67±0.002 and a specificity of 0.54±0.003. There were 301 gene transcripts identified across the 100 panels. Pathway analysis of the 301 gene transcripts identified clathrin coated vesicles formation, CDC42 in cellular processes and regulation of actin cytoskeleton by Rho GTPases as the top ranked pathways. The pre-challenge classifier out-performed the post-challenge classifier in the internal deep cross-validation as depicted by the classification performance measures. The lower performance of the post-challenge classifier in discriminating ERs from DRs may be due to a dilution of signal, given that both responder groups are undergoing an immune response to allergen inhalation. Incorporating changes in cellular composition and gene isoform expression estimates may improve classification performance and also reveal new insights into the mechanisms of the late phase asthmatic response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".